title: Modeling Alzheimer's Disease Progression Using Disease Onset Time and Disease Trajectory Concepts Applied to CDR-SOB Scores From ADNI.
abstract: Disease-onset time (DOT) and disease trajectory concepts were applied to derive an Alzheimer's disease (AD) progression population model using the clinical dementia rating scale-sum of boxes (CDR-SOB) from the AD neuroimaging initiative (ADNI) database. The model enabled the estimation of a DOT and a disease trajectory for each patient. The model also allowed distinguishing fast and slow-progressing subpopulations according to the functional assessment questionnaire, normalized hippocampal volume, and CDR-SOB score at study entry. On the basis of these prognostic factors, 81% of the mild cognitive impairment (MCI) subjects could correctly be assigned to slow or fast progressers, and 77% of MCI to AD conversions could be predicted whereas the model described correctly 84% of the conversions. Finally, synchronization of the biomarker-time profiles on estimated individual DOT virtually expanded the population observation period from 3 to 8 years. DOT-disease trajectory model is a powerful approach that could be applied to many progressive diseases.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e78; doi:10.1038/psp.2013.54; advance online publication 2 October 2013.
authors.affiliation: Life Sciences Services, SGS Exprimo NV, Mechelen, Belgium.
authors.forename: I
authors.initials: I
authors.lastname: Delor
authors.forename: J-E
authors.initials: JE
authors.lastname: Charoin
authors.forename: R
authors.initials: R
authors.lastname: Gieschke
authors.forename: S
authors.initials: S
authors.lastname: Retout
authors.forename: P
authors.initials: P
authors.lastname: Jacqmin